This work introduces a machine learning method for indirect test pattern generation in analog and mixed-signal circuits. The proposed method employs a low-cost test generation tool to simulate circuit ...

The training of molecular models of quantum mechanical properties based on statistical machine learning requires large data sets which exemplify the map from chemical structure to molecular property.

This was a mixed-methods analysis of insurance-related data collected from a cohort of English-speaking YA (currently age 18-39 years) blood cancer survivors, ≥3 years from diagnosis, recruited from ...

FedERA is a modular and fully customizable open-source FL framework, aiming to address these issues by offering comprehensive support for heterogeneous edge devices and incorporating both standalone ...

Deep learning models, especially those large-scale and high-performance ones, can be very costly to train, demanding a considerable amount of data and computational resources. As a result, deep ...

News Release 4-Jun-2025 University of Washington grad receives ACM Doctoral Dissertation Award for developing machine learning algorithms to improve mental health ...

Jennifer Schechter cofounded Integrate Health in 2004 alongside a community of people living with HIV/AIDS and is currently its CEO. Since then, she has led Integrate Health’s expansion across Togo ...

Development of a Biology-Guided Machine Learning Predictive Model for the Biosensor Dynamic Response Initial Experimental Design The observed biosensor dynamic responses for genetic and context ...